{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "\n",
    "%matplotlib inline\n",
    "\n",
    "plt.rcParams['figure.figsize'] = (4, 4)\n",
    "plt.rcParams['figure.dpi'] = 150\n",
    "plt.rcParams['lines.linewidth'] = 3\n",
    "sns.set()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = sns.load_dataset(\"titanic\")\n",
    "df = df[[\"age\", \"fare\", \"pclass\", \"sex\", \"survived\"]]\n",
    "df = df.dropna()\n",
    "df['sex'] = df['sex'].replace(\"male\", 0)\n",
    "df['sex'] = df['sex'].replace(\"female\", 1)\n",
    "np.random.seed(23)\n",
    "df_train, df_test = np.split(df, [600])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Suppose we want to compare the performance of several different models.\n",
    "\n",
    "One way is by individually performing a GridSearchCV on each model type."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.7916666666666666"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "\n",
    "decision_tree = DecisionTreeClassifier()\n",
    "parameters = {'min_impurity_decrease': [0, 0.01, 0.02, 0.05, 0.1]}\n",
    "\n",
    "dt_model_finder = GridSearchCV(decision_tree, parameters, cv=10)\n",
    "dt_model_finder.fit(df_train[[\"age\", \"fare\", \"pclass\", \"sex\"]],\n",
    "                    df_train[\"survived\"])\n",
    "dt_model_finder.best_score_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.79"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.pipeline import Pipeline\n",
    "from sklearn.preprocessing import PolynomialFeatures\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "\n",
    "logistic_regression_model = Pipeline([('scale', StandardScaler()),\n",
    "                                      ('model', LogisticRegression())])\n",
    "\n",
    "parameters = {'model__C': 10**np.linspace(-7, 5, 100)}\n",
    "lr_model_finder = GridSearchCV(logistic_regression_model, parameters, cv=10)\n",
    "lr_model_finder.fit(df_train[[\"age\", \"fare\", \"pclass\", \"sex\"]],\n",
    "                    df_train[\"survived\"])\n",
    "lr_model_finder.best_score_\n",
    "\n",
    "#Note, above we use GridSearchCV instead of LogisticRegressionCV. That is, the code above is\n",
    "#almost the same thing as:\n",
    "#logistic_regression_model = Pipeline([\n",
    "#    ('scale', StandardScaler()),\n",
    "#    ('model', LogisticRegressionCV(Cs = 10**np.linspace(-7, 5, 100)))\n",
    "#])\n",
    "#logistic_regression_model.fit(df_train[[\"age\", \"fare\", \"pclass\",  \"sex\"]], df_train[\"survived\"]);\n",
    ";"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also see all of the cross validation scores with `cv_results_`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'mean_fit_time': array([0.00319045, 0.00259037, 0.00249336, 0.00229244, 0.00199478]),\n",
       " 'std_fit_time': array([9.75647641e-04, 8.00442705e-04, 4.98605002e-04, 4.55217542e-04,\n",
       "        3.38016674e-07]),\n",
       " 'mean_score_time': array([0.00099804, 0.00109773, 0.00109727, 0.0008976 , 0.00079913]),\n",
       " 'std_score_time': array([0.00044586, 0.0005351 , 0.00069842, 0.00053707, 0.00039959]),\n",
       " 'param_min_impurity_decrease': masked_array(data=[0, 0.01, 0.02, 0.05, 0.1],\n",
       "              mask=[False, False, False, False, False],\n",
       "        fill_value='?',\n",
       "             dtype=object),\n",
       " 'params': [{'min_impurity_decrease': 0},\n",
       "  {'min_impurity_decrease': 0.01},\n",
       "  {'min_impurity_decrease': 0.02},\n",
       "  {'min_impurity_decrease': 0.05},\n",
       "  {'min_impurity_decrease': 0.1}],\n",
       " 'split0_test_score': array([0.68333333, 0.71666667, 0.78333333, 0.8       , 0.8       ]),\n",
       " 'split1_test_score': array([0.73333333, 0.73333333, 0.73333333, 0.76666667, 0.76666667]),\n",
       " 'split2_test_score': array([0.75      , 0.71666667, 0.75      , 0.75      , 0.8       ]),\n",
       " 'split3_test_score': array([0.75      , 0.83333333, 0.83333333, 0.8       , 0.8       ]),\n",
       " 'split4_test_score': array([0.8       , 0.83333333, 0.83333333, 0.85      , 0.85      ]),\n",
       " 'split5_test_score': array([0.85      , 0.81666667, 0.81666667, 0.73333333, 0.73333333]),\n",
       " 'split6_test_score': array([0.78333333, 0.78333333, 0.78333333, 0.78333333, 0.78333333]),\n",
       " 'split7_test_score': array([0.78333333, 0.81666667, 0.81666667, 0.75      , 0.75      ]),\n",
       " 'split8_test_score': array([0.81666667, 0.76666667, 0.76666667, 0.7       , 0.7       ]),\n",
       " 'split9_test_score': array([0.7       , 0.8       , 0.8       , 0.78333333, 0.78333333]),\n",
       " 'mean_test_score': array([0.765     , 0.78166667, 0.79166667, 0.77166667, 0.77666667]),\n",
       " 'std_test_score': array([0.04913134, 0.04374802, 0.03270236, 0.03947573, 0.03958114]),\n",
       " 'rank_test_score': array([5, 2, 1, 4, 3])}"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dt_model_finder.cv_results_"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Approach 2: Using a Dictionary of Dictionaries to Compare Many Model Types"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "\n",
    "all_models = {\n",
    "    'DecisionTree':\n",
    "        DecisionTreeClassifier(),\n",
    "    'RandomForest':\n",
    "        RandomForestClassifier(),\n",
    "    'LogisticRegression':\n",
    "        Pipeline([('scale', StandardScaler()),\n",
    "                  ('model', LogisticRegression())]),\n",
    "    'KNearestNeighbors':\n",
    "        KNeighborsClassifier()\n",
    "}\n",
    "\n",
    "all_params = {\n",
    "    'RandomForest': {\n",
    "        \"n_estimators\": [50, 100, 200],\n",
    "        'min_impurity_decrease': [0, 0.01, 0.02, 0.05, 0.1]\n",
    "    },\n",
    "    'DecisionTree': {\n",
    "        'min_impurity_decrease': [0, 0.01, 0.02, 0.05, 0.1]\n",
    "    },\n",
    "    'LogisticRegression': {\n",
    "        'model__C': 10**np.linspace(-7, 5, 100)\n",
    "    },\n",
    "    'KNearestNeighbors': {\n",
    "        'n_neighbors': [3, 4, 5, 8, 10]\n",
    "    }\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "best parameters are: DecisionTreeClassifier(ccp_alpha=0.0, class_weight=None, criterion='gini',\n",
      "                       max_depth=None, max_features=None, max_leaf_nodes=None,\n",
      "                       min_impurity_decrease=0.02, min_impurity_split=None,\n",
      "                       min_samples_leaf=1, min_samples_split=2,\n",
      "                       min_weight_fraction_leaf=0.0, presort='deprecated',\n",
      "                       random_state=None, splitter='best')\n",
      "accuracy is: 0.7916666666666666\n",
      "best parameters are: RandomForestClassifier(bootstrap=True, ccp_alpha=0.0, class_weight=None,\n",
      "                       criterion='gini', max_depth=None, max_features='auto',\n",
      "                       max_leaf_nodes=None, max_samples=None,\n",
      "                       min_impurity_decrease=0.01, min_impurity_split=None,\n",
      "                       min_samples_leaf=1, min_samples_split=2,\n",
      "                       min_weight_fraction_leaf=0.0, n_estimators=200,\n",
      "                       n_jobs=None, oob_score=False, random_state=None,\n",
      "                       verbose=0, warm_start=False)\n",
      "accuracy is: 0.7983333333333333\n",
      "best parameters are: Pipeline(memory=None,\n",
      "         steps=[('scale',\n",
      "                 StandardScaler(copy=True, with_mean=True, with_std=True)),\n",
      "                ('model',\n",
      "                 LogisticRegression(C=0.016297508346206434, class_weight=None,\n",
      "                                    dual=False, fit_intercept=True,\n",
      "                                    intercept_scaling=1, l1_ratio=None,\n",
      "                                    max_iter=100, multi_class='auto',\n",
      "                                    n_jobs=None, penalty='l2',\n",
      "                                    random_state=None, solver='lbfgs',\n",
      "                                    tol=0.0001, verbose=0, warm_start=False))],\n",
      "         verbose=False)\n",
      "accuracy is: 0.79\n",
      "best parameters are: KNeighborsClassifier(algorithm='auto', leaf_size=30, metric='minkowski',\n",
      "                     metric_params=None, n_jobs=None, n_neighbors=10, p=2,\n",
      "                     weights='uniform')\n",
      "accuracy is: 0.67\n"
     ]
    }
   ],
   "source": [
    "for name in all_models.keys():\n",
    "    model = all_models[name]\n",
    "    params = all_params[name]\n",
    "    gscv = GridSearchCV(estimator=model, param_grid=params, cv=10)\n",
    "    gscv.fit(df_train[[\"fare\", \"age\", \"pclass\", \"sex\"]], df_train[\"survived\"])\n",
    "    print(f\"best parameters are: {gscv.best_estimator_}\")\n",
    "    print(f\"accuracy is: {gscv.best_score_}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Above, we see the Random Forest model does slightly better than a decision tree or logistic regression model, with average cross-validation accuracy of 0.805."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Beyond Accuracy: Recall, Precision, and Sensitivity (and more)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "best_decision_tree = dt_model_finder.best_estimator_\n",
    "decision_tree_predictions = best_decision_tree.predict(\n",
    "    df_train[[\"age\", \"fare\", \"pclass\", \"sex\"]])\n",
    "\n",
    "best_logistic_model = lr_model_finder.best_estimator_\n",
    "logistic_predictions = best_logistic_model.predict(\n",
    "    df_train[[\"age\", \"fare\", \"pclass\", \"sex\"]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.7916666666666666"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.metrics import accuracy_score\n",
    "accuracy_score(df_train[\"survived\"], decision_tree_predictions)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.79"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "accuracy_score(df_train[\"survived\"], logistic_predictions)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[349,   7],\n",
       "       [118, 126]], dtype=int64)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.metrics import confusion_matrix\n",
    "cm_dt = confusion_matrix(df_train[\"survived\"], decision_tree_predictions)\n",
    "cm_dt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 600x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(cm_dt, annot=True, fmt=\"d\", cmap=\"Blues\", cbar=False)\n",
    "plt.ylabel('True')\n",
    "plt.xlabel('Predicted')\n",
    "sns.set(font_scale=2)\n",
    "plt.savefig(\"cm_dt.png\", dpi=300, bbox_inches=\"tight\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[310,  46],\n",
       "       [ 80, 164]], dtype=int64)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cm_lr = confusion_matrix(df_train[\"survived\"], logistic_predictions)\n",
    "cm_lr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 600x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(cm_lr,\n",
    "            annot=True,\n",
    "            fmt=\"d\",\n",
    "            cmap=\"Blues\",\n",
    "            annot_kws={\"size\": 20},\n",
    "            cbar=False)\n",
    "plt.ylabel('True')\n",
    "plt.xlabel('Predicted')\n",
    "sns.set(font_scale=2)\n",
    "plt.savefig(\"cm_lr.png\", dpi=300, bbox_inches=\"tight\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 600x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap([[95, 0], [5, 0]],\n",
    "            annot=True,\n",
    "            fmt=\"d\",\n",
    "            cmap=\"Blues\",\n",
    "            annot_kws={\"size\": 20},\n",
    "            cbar=False)\n",
    "plt.ylabel('True')\n",
    "plt.xlabel('Predicted')\n",
    "sns.set(font_scale=2)\n",
    "plt.savefig(\"cm_ex2.png\", dpi=300, bbox_inches=\"tight\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Effect of Threshold on Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "def predict_with_threshold(probabilities, T):\n",
    "    p1 = probabilities[:, 1]\n",
    "    return 1 * (p1 > T)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 1, 1])"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "predict_with_threshold(np.array([[0.6, 0.4], [0.3, 0.7], [0.1, 0.9]]), 0.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 0, 1])"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "predict_with_threshold(np.array([[0.6, 0.4], [0.3, 0.7], [0.1, 0.9]]), 0.75)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "lm_probabilities = best_logistic_model.predict_proba(\n",
    "    df_train[[\"age\", \"fare\", \"pclass\", \"sex\"]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics import precision_score\n",
    "from sklearn.metrics import recall_score\n",
    "\n",
    "\n",
    "def show_confusion_matrix_and_print_accuracy_and_recall(reality, predictions):\n",
    "    cm = confusion_matrix(reality, predictions)\n",
    "    sns.heatmap(cm,\n",
    "                annot=True,\n",
    "                fmt=\"d\",\n",
    "                cmap=\"Blues\",\n",
    "                annot_kws={\"size\": 20},\n",
    "                cbar=False)\n",
    "    plt.ylabel('True')\n",
    "    plt.xlabel('Predicted')\n",
    "    sns.set(font_scale=2)\n",
    "    print(f\"Precision: {precision_score(reality, predictions)}\")\n",
    "    print(f\"Recall: {recall_score(reality, predictions)}\")\n",
    "    #plt.savefig(\"cm_t50.png\", dpi = 300, bbox_inches = \"tight\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Precision: 0.780952380952381\n",
      "Recall: 0.6721311475409836\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 600x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "t50_predictions = predict_with_threshold(lm_probabilities, 0.50)\n",
    "show_confusion_matrix_and_print_accuracy_and_recall(df_train[\"survived\"],\n",
    "                                                    t50_predictions)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Precision: 0.9214285714285714\n",
      "Recall: 0.5286885245901639\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 600x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "show_confusion_matrix_and_print_accuracy_and_recall(\n",
    "    df_train[\"survived\"], predict_with_threshold(lm_probabilities, 0.60))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Precision: 0.9615384615384616\n",
      "Recall: 0.3073770491803279\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 600x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "t70_predictions = predict_with_threshold(lm_probabilities, 0.70)\n",
    "show_confusion_matrix_and_print_accuracy_and_recall(df_train[\"survived\"],\n",
    "                                                    t70_predictions)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Precision: 0.9428571428571428\n",
      "Recall: 0.13524590163934427\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 600x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "t80_predictions = predict_with_threshold(lm_probabilities, 0.80)\n",
    "show_confusion_matrix_and_print_accuracy_and_recall(df_train[\"survived\"],\n",
    "                                                    t80_predictions)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Or we can generate an entire precision recall curve from the probabilities using sklearn:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 600x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.metrics import precision_recall_curve\n",
    "\n",
    "precision, recall, thresholds = precision_recall_curve(df_train[\"survived\"],\n",
    "                                                       lm_probabilities[:, 1])\n",
    "plt.plot(recall, precision, '*')\n",
    "plt.xlabel(\"recall\")\n",
    "plt.ylabel(\"precision\")\n",
    "plt.text(recall[467], precision[467], f\"T = {thresholds[467]:.2f}\")\n",
    "plt.text(recall[400], precision[400], f\"T = {thresholds[400]:.2f}\")\n",
    "plt.text(recall[540], precision[540], f\"T = {thresholds[540]:.2f}\")\n",
    "plt.ylim(-0.03, 1.05)\n",
    "plt.savefig(\"precision_vs_recall_lm_better.png\", dpi=300, bbox_inches=\"tight\")\n",
    "#https://scikit-learn.org/stable/auto_examples/model_selection/plot_precision_recall.html#sphx-glr-auto-examples-model-selection-plot-precision-recall-py"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "One common use for a precision-recall curve is to compare two models independent of the specific threshold that they use. For example, let's consider a bad model that just randomly guesses."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "class RandomGuesser():\n",
    "\n",
    "    def predict(self, x):\n",
    "        return np.random.random(len(x))\n",
    "\n",
    "\n",
    "rg = RandomGuesser()\n",
    "random_guesses = rg.predict(df_train[[\"age\", \"fare\", \"pclass\", \"sex\"]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.2148441 , 0.09463218, 0.48859712, 0.89034246, 0.84709382])"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "random_guesses[0:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'precision')"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 600x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "precision_lm, recall_lm, thresholds_lm = precision_recall_curve(\n",
    "    df_train[\"survived\"], lm_probabilities[:, 1])\n",
    "precision_rg, recall_rg, thresholds_rg = precision_recall_curve(\n",
    "    df_train[\"survived\"], random_guesses)\n",
    "plt.plot(recall_lm, precision_lm)\n",
    "plt.plot(recall_rg, precision_rg, 'k')\n",
    "plt.legend([\"Logistic Regression\", \"Random Guess\"])\n",
    "plt.text(recall[40], precision[40], f\"T = {thresholds[40]:.2f}\")\n",
    "plt.text(recall[400], precision[400], f\"T = {thresholds[400]:.2f}\")\n",
    "plt.text(recall[540], precision[540], f\"T = {thresholds[540]:.2f}\")\n",
    "plt.xlabel(\"recall\")\n",
    "plt.ylabel(\"precision\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's compare the precision-recall curve for the random guesser and the random forest classifier below:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "rf = RandomForestClassifier(min_impurity_decrease=0.01, n_estimators=200)\n",
    "rf.fit(df_train[[\"age\", \"fare\", \"pclass\", \"sex\"]], df_train[\"survived\"])\n",
    "rf_predictions = rf.predict_proba(df_train[[\"age\", \"fare\", \"pclass\", \"sex\"]])[:,\n",
    "                                                                              1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1e742a2a408>"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 600x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "precision_rf, recall_rf, thresholds_rf = precision_recall_curve(\n",
    "    df_train[\"survived\"], rf_predictions)\n",
    "precision_lm, recall_lm, thresholds_lm = precision_recall_curve(\n",
    "    df_train[\"survived\"], lm_probabilities[:, 1])\n",
    "\n",
    "plt.plot(recall_rf, precision_rf)\n",
    "plt.plot(recall_lm, precision_lm)\n",
    "\n",
    "#plt.text(recall[40], precision[40], f\"T = {thresholds[40]:.2f}\")\n",
    "#plt.text(recall[400], precision[400], f\"T = {thresholds[400]:.2f}\")\n",
    "#plt.text(recall[540], precision[540], f\"T = {thresholds[540]:.2f}\")\n",
    "plt.xlabel(\"recall\")\n",
    "plt.ylabel(\"precision\")\n",
    "plt.ylim(-0.03, 1.05)\n",
    "plt.legend([\"Random Forest\", \"Logistic Regression\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 600x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.metrics import roc_curve\n",
    "fpr_lm, tpr_lm, thresholds_lm = roc_curve(df_train[\"survived\"],\n",
    "                                          lm_probabilities[:, 1])\n",
    "fpr_rf, tpr_rf, thresholds_rf = roc_curve(df_train[\"survived\"], rf_predictions)\n",
    "\n",
    "plt.plot(fpr_rf, tpr_rf)\n",
    "plt.plot(fpr_lm, tpr_lm)\n",
    "\n",
    "plt.xlabel(\"False Positive Rate\")\n",
    "plt.ylabel(\"True Positive Rate\")\n",
    "plt.legend([\"Random Forest\", \"Logistic Regression\"])\n",
    "plt.savefig(\"roc_of_rf_vs_lr.png\", dpi=300, bbox_inches=\"tight\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Explainable AI"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Sometimes we prefer models that are more \"explinable\". That is, we have a clear understand of exactly how they generated their prediction probabilities."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[-3.28724731e-02, -1.66319009e-04, -1.26767158e+00,\n",
       "         2.48727307e+00]])"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "logistic_model = LogisticRegression(C=1e10)\n",
    "logistic_model.fit(df_train[[\"age\", \"fare\", \"pclass\", \"sex\"]],\n",
    "                   df_train[\"survived\"])\n",
    "logistic_model.coef_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([2.38881115])"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "logistic_model.intercept_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.91686878, 0.08313122]])"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "logistic_model.predict_proba([[30, 1, 3, 0]])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The 8% probability we get above can be simply explained in terms of the model coefficients, the data, and the intercept."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.08313122])"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def sigma(x):\n",
    "    return 1 / (1 + np.exp(-x))\n",
    "\n",
    "\n",
    "sigma(\n",
    "    np.sum(logistic_model.coef_ * np.array([30, 1, 3, 0])) +\n",
    "    logistic_model.intercept_)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "By contrast, the probabilities generated by the random forest are harder to interpret. There are generated by the votes of 100 separate decision trees."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "RandomForestClassifier(bootstrap=True, ccp_alpha=0.0, class_weight=None,\n",
       "                       criterion='gini', max_depth=None, max_features='auto',\n",
       "                       max_leaf_nodes=None, max_samples=None,\n",
       "                       min_impurity_decrease=0.0, min_impurity_split=None,\n",
       "                       min_samples_leaf=1, min_samples_split=2,\n",
       "                       min_weight_fraction_leaf=0.0, n_estimators=100,\n",
       "                       n_jobs=None, oob_score=False, random_state=None,\n",
       "                       verbose=0, warm_start=False)"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rf_model = RandomForestClassifier()\n",
    "rf_model.fit(df_train[[\"age\", \"fare\", \"pclass\", \"sex\"]], df_train[\"survived\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0], dtype=int64)"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rf_model.predict([[30, 1, 3, 0]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.62, 0.38]])"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rf_model.predict_proba([[30, 1, 3, 0]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
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 },
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